Optics and Precision Engineering, Volume. 31, Issue 13, 1973(2023)
Automatic segmentation of aggregate images with MET optimized by chaos SSA
Figures & Tables(15)
Table 1. Evaluation parameters
View tableView in ArticleTable 1. Evaluation parameters
方 法 F1 F2 Best AVG SD T/s Best AVG SD T/s PSO 8.75×10-11 3.47×10-9 6.08×10-9 69.945 2.64×10-1 1.56 8.07×10-1 68.919 GWO 4.93×10-45 4.01×10-43 9.02×10-43 64.120 4.12×10-12 6.52×10-11 8.46×10-11 60.733 WOA 1.07×10-126 9.61×10-111 6.10×10-110 23.023 2.07×10-1 4.79×10 2.44×10 23.022 MA 9.48×10-12 1.43×10-10 3.42×10-10 174.036 2.81×10 4.24×10 5.54 170.238 SSA 3.10×10-258 2.22×10-50 1.71×10-49 20.316 1.03×10-53 1.96×10-10 1.25×10-9 20.210 CASSA 0 9.93×10-53 6.72×10-39 19.162 3.76×10-27 6.38×10-13 3.79×10-11 20.661 CDLSSA 0 0 0 41.614 0 1.43×10-204 0 40.259 LSSA 0 0 0 21.367 0 0 0 20.497 方 法 F3 F4 Best AVG SD T/s Best AVG SD T/s PSO 9.17 5.51×10 8.35×10+1 72.211 -9.07×103 -7.86×103 6.17×102 72.674 GWO 2.52×10 2.65×10 7.21×10-1 64.341 -7.23×103 -6.02×103 5.78×102 64.946 WOA 2.60×10 2.70×10 7.08×10-1 26.039 -1.26 ×104 -9.25×103 1.46×103 25.942 MA 8.06×10-1 4.68×10 5.19×10+1 183.103 -1.11×104 -1.02×104 3.19×102 185.479 SSA 1.21×10-7 4.91×10-4 6.97×10-3 22.811 -9.91×103 -8.86×103 1.73×103 22.903 CASSA 1.19×10-7 7.40×10-4 2.01×10-3 22.548 -9.29×103 -9.76×103 1.86×103 22.432 CDLSSA 1.03×10-7 1.19×10-3 5.70×10-3 44.432 -1.26 ×104 -1.04×104 1.03×102 43.501 LSSA 1.16 ×10-8 4.45 ×10-4 1.91 ×10-3 23.025 -1.26 ×104 -1.08 ×104 1.00 ×102 23.011 方 法 F5 F6 Best AVG SD T/s Best AVG SD T/s PSO 2.49×10 5.63×10 1.36×10 70.819 1.04×10-11 1.07×10-1 1.98×10-1 100.284 GWO 0 7.56×10-1 2.06 62.135 1.68×10-6 2.53×10-2 1.52×10-2 94.983 WOA 0 0 0 23.341 6.67×10-4 1.66×10-2 1.13×10-2 50.255 MA 4.98 2.09×10 1.06×10 176.503 2.07×10-9 9.10×10-2 2.12×10-1 256.946 SSA 0 0 0 20.350 2.39×10-10 1.21×10-6 2.46×10-6 48.751 CASSA 0 0 0 20.543 9.53×10-11 5.80×10-7 2.56×10-6 48.613 CDLSSA 0 0 0 40.018 2.58×10-11 5.10×10-7 1.65×10-6 88.256 LSSA 0 0 0 20.155 1.09 ×10-12 3.70 ×10-8 9.65 ×10-7 48.639
Table 2. 时LSSA-MET与SSA-MET的阈值和适应度值
View tableView in ArticleTable 2. 时LSSA-MET与SSA-MET的阈值和适应度值
图像 参数 Renyi熵 对称交叉熵 Kapur熵 LSSA SSA LSSA SSA LSSA SSA No.1 阈值 41 74 115 150 186 227 35 62 95
131 171 228
30 56 92 121 154 185 32 55 92
113 149 172
41 73 102 133 161 192 39 72 94
124 169 191
适应度值 24.356 6 24.237 9 241 731.634 266 481.176 9 24.124 9 23.974 No.2 阈值 44 76 108 167 142 199 45 71 92
114 137 189
32 65 101 131 157 183 36 73 109
133 150 178
37 75 106 134 162 194 40 61 80
118 151 190
适应度值 24.305 9 23.971 1 239 635.992 8 262 853.106 6 24.091 3 23.926 6 No.3 阈值 37 71 140 14 173 208 39 71 104
137 169 201
25 43 81 109 143 173 29 53 91
126 139 166
38 70 105 136 168 199 43 77 100
124 150 185
适应度值 24.416 4 24.409 5 263 073.381 9 284 278.489 6 24.142 1 23.989 No.4 阈值 36 69 100 131 163 193 53 80 101
122 149 176
35 65 95 126 157 183 37 63 95
126 154 183
41 72 101 129 159 190 43 85 109
134 160 183
适应度值 24.088 9 23.795 7 183 027.266 6 183 338.434 2 23.824 8 23.693 1
Table 3. PSNR values
View tableView in ArticleTable 3. PSNR values
图像 K Renyi Entropy Symmetric Cross Entropy Kapur Entropy FCM LSSA SSA LSSA SSA LSSA SSA No.1 2 13.0 13.1 12.0 12.0 12.4 12.4 12.8 4 17.9 17.2 15.8 15.6 17.3 16.4 12.3 6 24.4 22.7 17.3 15.4 19.2 19.4 8.46 No 2 2 13.3 13.2 12.4 12.4 13.1 13.1 11.3 4 17.6 17.0 15.8 14.2 16.9 16.5 10.3 6 20.4 15.7 17.4 16.4 19.2 16.8 7.51 No.3 2 13.5 13.5 11.5 11.5 12.6 12.6 12.4 4 18.3 17.6 14.1 13.7 17.6 16.5 11.0 6 22.9 21.6 14.7 14.7 21.3 17.0 6.41 No.4 2 13.0 13.0 13.6 13.5 12.6 12.6 12.0 4 18.2 17.9 17.4 17.4 17.3 17.1 10.7 6 21.5 16.8 19.0 18.7 20.2 19.0 7.69 优值个数 9 1 7 0 7 1 —
Table 4. SSIM values
View tableView in ArticleTable 4. SSIM values
图像 K Renyi Entropy Symmetric Cross Entropy Kapur Entropy FCM LSSA SSA LSSA SSA LSSA SSA No.1 2 3.29×10-1 3.31 ×10-13.15×10-1 3.15×10-1 3.20×10-1 3.20×10-1 3.66×10-1 4 5.19 ×10-1 5.11×10-1 5.14 ×10-1 5.09×10-1 5.20 ×10-1 5.12×10-1 2.39×10-1 6 6.21 ×10-1 5.95×10-1 6.35 ×10-1 5.97×10-1 6.32 ×10-1 6.11×10-1 2.68×10-2 No 2 2 3.72 ×10-1 3.70×10-1 3.61×10-1 3.62 ×10-1 3.68×10-1 3.68×10-1 1.24×10-1 4 5.61 ×10-1 5.56×10-1 5.56 ×10-1 5.30×10-1 5.59 ×10-1 5.56×10-1 3.81×10-1 6 6.67 ×10-1 6.03×10-1 6.63 ×10-1 6.27×10-1 6.69 ×10-1 6.36×10-1 2.28×10-2 No.3 2 3.52×10-1 3.52×10-1 3.31×10-1 3.31×10-1 3.48×10-1 3.48×10-1 6.17×10-1 4 5.48×10-1 5.49 ×10-1 5.40 ×10-1 5.32×10-1 5.50 ×10-1 5.38×10-1 2.29×10-2 6 6.78 ×10-1 6.74×10-1 6.47 ×10-1 6.21×10-1 6.74 ×10-1 6.46×10-1 3.47×10-3 No.4 2 3.06×10-1 3.06×10-1 3.21 ×10-1 3.18×10-1 2.96×10-1 2.96×10-1 2.84×10-1 4 5.18 ×10-1 5.09×10-1 5.10 ×10-1 5.02×10-1 5.09 ×10-1 5.04×10-1 1.46×10-1 6 6.29 ×10-1 6.02×10-1 6.26 ×10-1 6.18×10-1 6.29 ×10-1 6.14×10-1 1.11×10-2 优值个数 8 2 9 1 8 0 —
Table 5. FSIM values
View tableView in ArticleTable 5. FSIM values
图像 K Renyi Entropy Symmetric Cross Entropy Kapur Entropy FCM LSSA SSA LSSA SSA LSSA SSA No.1 2 7.40×10-1 7.41 ×10-1 7.32×10-1 7.32×10-1 7.32×10-1 7.32×10-1 7.67×10-1 4 8.81 ×10-1 8.77×10-1 8.76 ×10-1 8.66×10-1 8.81 ×10-1 8.69×10-1 7.08×10-1 6 9.33 ×10-1 9.09×10-1 9.27 ×10-1 8.96×10-1 9.24 ×10-1 9.12×10-1 6.40×10-1 No 2 2 7.59 ×10-1 7.57×10-1 7.49×10-1 7.50 ×10-1 7.52×10-1 7.53 ×10-1 7.66×10-1 4 8.92 ×10-1 8.84×10-1 8.83 ×10-1 8.61×10-1 8.87 ×10-1 8.80×10-1 7.64×10-1 6 9.32 ×10-1 8.87×10-1 9.19 ×10-1 8.89×10-1 9.33 ×10-1 9.17×10-1 6.90×10-1 No.3 2 7.55×10-1 7.55×10-1 7.29×10-1 7.29×10-1 7.44×10-1 7.44×10-1 7.05×10-1 4 8.91 ×10-1 8.84×10-1 8.77 ×10-1 8.69×10-1 8.90 ×10-1 8.76×10-1 6.41×10-1 6 9.46 ×10-1 9.22×10-1 9.16 ×10-1 8.92×10-1 9.41 ×10-1 9.11×10-1 6.05×10-1 No.4 2 7.21×10-1 7.21×10-1 7.34 ×10-1 7.33×10-1 7.12 ×10-1 7.11×10-1 6.93×10-1 4 8.71 ×10-1 8.64×10-1 8.66 ×10-1 8.61×10-1 8.65 ×10-1 8.58×10-1 6.80×10-1 6 9.28 ×10-1 8.87×10-1 9.21 ×10-1 9.11×10-1 9.25 ×10-1 9.02×10-1 6.72×10-1 优值个数 9 1 9 1 9 1 —
Table 6.
T valuesView tableView in ArticleTable 6.
T valuesK Renyi Entropy Symmetric Cross Entropy Kapur Entropy FCM LSSA SSA LSSA SSA LSSA SSA 2 1.421 s 1.422 s 1.498 s 1.498 s 1.440 s 1.440 s 1.667 s 4 1.461 s 1.453 s 1.546 s 1.564 s 1.496 s 1.476 s 4.386 s 6 1.472 s 1.491 s 1.618 s 1.603 s 1.507 s 1.489 s 8.602 s 优值个数 2 1 1 1 0 2 —
Table 7. Parameter statistical mean of LSSA-MET
View tableView in ArticleTable 7. Parameter statistical mean of LSSA-MET
算 法 PSNR SSIM FSIM T/s LSSA-Renyi熵 1.78 ×105.08 ×10-1 8.54 ×10-1 1.451 LSSA-对称交叉熵 1.51×10 5.02×10-1 8.44×10-1 1.554 LSSA-Kapur熵 1.66×10 5.06×10-1 8.49×10-1 1.481
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Mengfei WANG, Weixing WANG, Limin LI. Automatic segmentation of aggregate images with MET optimized by chaos SSA[J]. Optics and Precision Engineering, 2023, 31(13): 1973
Paper Information
Category: Information Sciences
Received: Aug. 30, 2022
Accepted: --
Published Online: Jul. 26, 2023
The Author Email: Weixing WANG (lilimin@wzu.edu.cn), Limin LI (lilimin@wzu.edu.cn)
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